REFRAME → BUILD → TEST → REFINE

DEPLOYMENT STRATEGIST.AI ENGINEER.FOUNDER.

01 / SPHOENIX

01 / OBSERVE02 / CONNECT03 / ACT

TURNCOMPLEXITYINTO STRATEGY.

I turn ambiguous problems into usable systems.
Reframe. Build. Test against reality.

01 — EDITORIAL & LEADERSHIPBOTNEWS.AI

FOR THE PEOPLE BUILDING WHAT’S NEXT

DEEP TECH.
RARE
INSIGHT.

BotNews is where I publish the research you’ll explore here. As founder and editor-in-chief, I shape the stories, lead engineer-writers, and make highly technical ideas useful to the people building what’s next.

botnews.ai

THE READING ROOM

WORLD MODELSSPHOENIX

How to catch a world model lying to you.

A field guide to questioning generated futures. Work backward from the footage to the action—and find the frame where trust ends.

01 / 04

A READERSHIP ACROSS ROBOTICS, AI & SECURITY

Boston DynamicsMidjourneyDOWOpenAICrowdStrikeCerebrasWorld Labs

Reader affiliations · not institutional endorsements

02 — STRATEGIC INTELLIGENCEFROM SIGNAL TO SOLUTION

THINK THROUGH IT WITH ME

Ask the right question.

A shelf count is a signal. The real question: which drinks can this store actually fulfill?

Choose 01–04 to build the ontology.SCROLL TO BUILD THE NEXT LAYER

FULFILLMENT ONTOLOGY LIVE DEMONSTRATION

Ingredient

A counted item becomes a dependency: SKU, quantity, expiry, and the recipes that require it.

CASE STUDY / STARBUCKSThe bottle was never the business problem.

03 — WORLD MODELS & RELIABILITYQUESTION THE CONVINCING

LOOKS RIGHT.
IS IT?

In my field guide, How to Catch a World Model Lying to You, I explain how SC3-Eval checks whether a simulated robot is still following its commands. Catching that mismatch helps engineers evaluate a robot’s behavior without mistaking convincing video for trustworthy evidence.

Based on SC3-Eval by Wei-Cheng Tseng & collaborators.

TRY IT Slide through this example. When the dashed action inferred from the video separates from the yellow command, the simulated rollout is no longer trustworthy.

ACTION ↔ RECONSTRUCTION ILLUSTRATIVE EXPLAINER

— Commanded action┄ Reconstructed action

✓ ACTIONS AGREE — CONTINUEFRAME 035

HOW TO CATCH A WORLD MODEL LYING TO YOU

“A score that ranks hands them a leaderboard. A witness that names the failure hands them a lead.”

SAME INSIGHT. DIFFERENT LENS.

Complexity, translated.

Before you invest in the next training run, ask whether the evaluation tells you what actually needs fixing.

RESEARCH / THE RELIABILITY KILL CHAIN

How does a wrong answer
become accepted reality?

I wrote The Reliability Kill Chain to ask how AI-generated compliance could be trusted at the Department of War (DoW). Building on Princeton University’s AI-agent reliability research, I trace how one unsupported security claim can pass review, authorize a system, and spread to others—and propose evidence checks to interrupt it.

Research foundation: Stephan Rabanser, Sayash Kapoor & colleagues · Princeton University

TRY IT Choose a stage, then “Break the chain” to see the proposed safeguard that could stop the error before it becomes a security gap.

STAGE 1 OF 7

The wrong evidence gets in.

A poisoned or outdated source enters the knowledge base.

Choose a stage. Reveal the safeguard that interrupts it.

Concept lunar landscape with a distant habitat

04 — SPATIAL INTELLIGENCEAN EVOLVING EXPLORATION

FROM UNDERSTANDING A WORLD TO ACTING IN IT

MOON
TOLOGY.

Rooted in DIU, U.S. Space Force, and NASA research, Moontology explores a practical problem in autonomy: how do we know a robot did what the system claims—and keep its actions within the authority it was given?

I’m developing a bridge between simulation and the physical world. dimOS connects a quadruped robot as the embodied layer; an articulated URDF model represents it in the 3D environment. Astra reasons through robotic scenarios, while the ontology connects observations, permissions, and outcomes so decisions can be checked against evidence.

MISSION LOG / NEXT CHAPTER IN DEVELOPMENT

Current focus: revocable task authority and independent verification of what a robot actually did.

Concept environment artwork

05 — CREATIVE TECHNOLOGYIDEAS YOU CAN STEP INSIDE

SERIOUS
ABOUT PLAY.

Helped run a six-figure Fortnite UEFN map. Engineered gameplay, shaped map strategy around player retention, and managed brand deals.

Fortnite / UEFN

INTERACTIVE WORLDS · VERSE · PRODUCT

Generated minigame island concept with branching paths, a central arena and elevated platforms

P01

P02

P03

P04

ARENA_01 / SANDBOXDRAG TO ORBIT

GENERATED CONCEPT / SIMULATED PLAYERS

using { /Fortnite.com/Devices }

arena_loop := class(creative_device):
  OnBegin<override>()<suspends>:void =
    Print("Let’s build something worth playing.")

Built and shipped game modes, NPC behaviors, spawn logic, and player interaction loops in Verse. Tuned gameplay under live-user conditions.

CREATIVE GENERATION / ARCHIVE

Imagination,
made visible.

As an early DALL·E artist contributor and creative tester, I explored prompt sensitivity, controllability, and visual storytelling. Created as @sphoenixai for OpenAI social co-posts.